Abstract

Clustering is one basic and important data mining approach used independently as well as the pre-processing stage in many data mining applications. The clustering process basically divides the available dataset into smaller subsets called clusters. These clusters are generally substantially different from one other. In this present work, the clustering is performed on text documents. Text document clustering basically divide the available documents in sub groups based on clustering parameters. The document clustering includes number of basic phenomenon such as document organization, topic extraction and the information retrieval. In this, an improvement clustering approach is defined over the basic clustering approach. The basic clustering approaches that we have to improve in this work areK-Means Clustering and C-Means Clustering. The improvement is here done with the inclusion of PSO (Particle Swarm Optimization)

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